Power Analysis for Cluster Randomized Trials with Multiple Primary Endpoints
Date: 1 April, Friday
Time: 2pm AEDT
Speaker: Professor Song Zhang (UT Southwestern Medical Center)
Cluster randomized trials (CRTs) are widely used in different areas of medicine and public health. Recently, with the increasing complexity of medical therapies and technological advances in monitoring multiple outcomes, many clinical trials attempt to evaluate multiple primary endpoints. In this study we present a power analysis method for CRTs with K > 2 binary co-primary endpoints. It is developed based on the GEE (generalized estimating equation) approach, and three types of correlations are considered: inter-subject correlation within each endpoint, intra-subject correlation across endpoints, and inter-subject correlation across endpoints. A closed-form joint distribution of the K test statistics is derived, which facilitates the evaluation of power and type I error for arbitrarily constructed hypotheses. We further present a theorem that characterizes the relationship between various correlations and testing power. We assess the performance of the proposed power analysis method based on extensive simulation studies. An application example to a real clinical trial is presented.
Short Bio: Dr. Song Zhang is a professor of biostatistics from the Department of Population and Data Sciences, University of Texas Southwestern Medical Center. He received his Ph.D. in statistics from the University of Missouri-Columbia in 2005. His research interest includes Bayesian hierarchical models with application to disease mapping, missing data imputation, joint modeling of longitudinal and survival outcomes, and genomic pathway analysis, as well as experimental design methods for clinical trials with clustered/longitudinal outcomes, different types of outcome measures, missing data patterns, correlation structures, and financial constraints. He has co-authored a book titled "Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research" (Chapman & Hall/CRC). As the principal investigator, Dr. Zhang has received funding from PCORI, NIH, and NSF to support his research.
Zoom link: https://uni-sydney.zoom.us/j/81356717273
Date: 1 April, Friday
Time: 2pm AEDT
Speaker: Professor Song Zhang (UT Southwestern Medical Center)
Cluster randomized trials (CRTs) are widely used in different areas of medicine and public health. Recently, with the increasing complexity of medical therapies and technological advances in monitoring multiple outcomes, many clinical trials attempt to evaluate multiple primary endpoints. In this study we present a power analysis method for CRTs with K > 2 binary co-primary endpoints. It is developed based on the GEE (generalized estimating equation) approach, and three types of correlations are considered: inter-subject correlation within each endpoint, intra-subject correlation across endpoints, and inter-subject correlation across endpoints. A closed-form joint distribution of the K test statistics is derived, which facilitates the evaluation of power and type I error for arbitrarily constructed hypotheses. We further present a theorem that characterizes the relationship between various correlations and testing power. We assess the performance of the proposed power analysis method based on extensive simulation studies. An application example to a real clinical trial is presented.
Short Bio: Dr. Song Zhang is a professor of biostatistics from the Department of Population and Data Sciences, University of Texas Southwestern Medical Center. He received his Ph.D. in statistics from the University of Missouri-Columbia in 2005. His research interest includes Bayesian hierarchical models with application to disease mapping, missing data imputation, joint modeling of longitudinal and survival outcomes, and genomic pathway analysis, as well as experimental design methods for clinical trials with clustered/longitudinal outcomes, different types of outcome measures, missing data patterns, correlation structures, and financial constraints. He has co-authored a book titled "Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research" (Chapman & Hall/CRC). As the principal investigator, Dr. Zhang has received funding from PCORI, NIH, and NSF to support his research.
Zoom link: https://uni-sydney.zoom.us/j/81356717273